Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines
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Mahmoud Azab, Stephane Dadian, Vivi Nastase, Larry An, Rada Mihalcea. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.
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Azab et al developed a data set and a baseline system consisting of narrative answers annotated with family histories from FH questionnaires, based on patient-provided information.
“For example, Azab et al [12] have developed a data set and a baseline system consisting of narrative answers annotated with family histories from FH questionnaires [12], which is based on patient-provided information.”
From Family History Extraction From Synthetic Clinical Narratives Using Natural Language Processing: Overview and Evaluation of a Challenge Data Set and Solutions for the 2019 National NLP Clinical Challenges (n2c2)/Open Health Natural Language Processing (OHNLP) Competition (2021) · cites this paper as [12]
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- Authors
- Azab, M., Dadian, S., Nastase, V., An, L., & Mihalcea, R.
- Affiliations
- University of Michigan (US)
- ORCID
- Mihalcea, Rada
- Venue
- Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
- Published
- 2019
- OpenAlex
- W2970726561
- Cited by
- 5
- References
- 19
- Citations by year
- 2023: 1 · 2021: 1 · 2020: 3
- FWCI
- 3.01
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Conference on Empirical Methods in Natural Language Processing (EMNLP) (publishedVersion, cc-by)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Keywords
- natural language interaction, clinical notes, dataset construction, information extraction, family history (medicine)
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